text: Given the flux expression, it is possible to derive the flux control coefficients by differentiation and scaling of the flux expression. This can be done for the general case of  steps:
  This result yields two corollaries:
  * The sum of the flux control coefficients is one. This confirms the summation theorem.
  * The value of an individual flux control coefficient in a linear reaction chain is greater than 0 or less than one: 
  For the three-step linear chain, the flux control coefficients are given by:
  where  is given by:
  Given these results, there are some patterns:
  * If all three steps have large equilibrium constants, that is , then  tends to one and the remaining coefficients tend to zero.
  * If the equilibrium constants are smaller, control tends to get distributed across all three steps.
  With more moderate equilibrium constants, perturbations can travel upstream as well as downstream. For example, a perturbation at the last step, , is better able to influence the reaction rates upstream, which results in an alteration in the steady-state flux.
  An important result can be obtained if all  are set as equal to each other. Under these conditions, the flux control coefficient is proportional to the numerator. That is:
  If it is assumed that the equilibrium constants are all greater than 1.0, as earlier steps have more  terms, it must mean that earlier steps will, in general, have high larger flux control coefficients. In a linear chain of reaction steps, flux control will tend to be biased towards the front of the pathway.  From a metabolic engineering or drug-targeting perspective, preference should be given to targeting the earlier steps in a pathway since they have the greatest effect on pathway flux. Note that this rule only applies to pathways without negative feedback loops.